A multilevel analysis of job satisfaction in Britain - WERS 2004

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minority co-workers affects the job satisfaction of whites adversely but that suchan effect vanishes once they control for the characteristics of jobs.3. The data and sampleThe data used in this study come from the 2004 British Workplace employmentrelations Survey, WERS 2004 (Department of Trade and Industry, 2005). It is themost recent survey in a series of five surveys of its kind. 6 The survey is regardedas one of the most authoritative sources of information on employment relationsin Great Britain. It offers linked employer-employee data drawn from apopulation of 700,000 workplaces (33 per cent of all workplaces in Britain) and22.5 million employees (89 per cent of all employees in employment) (Kersley etal. 2006). 7The sample of workplaces covered by the WERS 2004 survey is a randomsample of the 33 per cent of all workplaces in Britain stratified by workplace sizeand industry, with over-representation of large workplaces to make statisticallyreliable comparisons with their smaller counterparts. The probability of selectionof an employee in the survey is a product of the probability of the employee’sworkplace being selected and the probability of selection of the employee. Thisweight has been used in the empirical analysis in this study, to be able toextrapolate the findings to the population of workplaces in Britain with at leastfive employees (Kersley et al. 2006, Bryson et al. 2004).The WERS 2004 survey has covered a whole host of issues relating to bothemployers and employees, thereby allowing the inclusion of an array ofindividual and workplace level attributes into the analysis undertaken in thisstudy. The estimation sub-sample used in this study comprises of 20,692employees in some 1727 workplaces with complete information on all thevariables of interest that are summarised in Table A3 in the Appendix.The WERS 2004 survey asked each employee to rate, on a five-point scale from‘very satisfied’ to ‘very dissatisfied’, regarding how satisfied they were on eightaspects of their job including: (i) the sense of achievement they get from theirwork; (ii) the scope for using their own initiative; (iii) the amount of influencethey have over their job; (iv) the training they receive; (v) the amount of pay theyreceive; (vi) their job security; (vii) their involvement in decision making; and(viii) their work itself. An overall job satisfaction indicator has been generatedfrom these eight facets of job satisfaction in a way similar to that of Bryson et al.(2004). 8 For the purpose of the empirical analysis undertaken, the ordinalinter-group interaction exists between minorities and, in this case, whites; thereby impactingindividual job attitudes.6 Innovations in the most recent survey (WERS 2004) include, among others, the inclusion ofsmaller firms with between five and nine employees and the sampling of greater numbers of nonunionemployee representatives(Kersley et al. 2006).7 The survey population was all British workplaces but those in Agriculture, hunting & forestry,fishing, mining & quarrying, private households with employed persons, extra-territorialorganizations and bodies comprising of at least five employees (Kersley et al. 2006).8 Where a dummy variable equal to 1 if an employee was either ‘very satisfied’ or ‘satisfied’ and0 otherwise has been generated for each aspects of job satisfaction and eight such dummyvariables have been added to give an overall job satisfaction indicator.6
‘overall’ as well as each of the ‘facet’ satisfaction variables with five categorieshas been collapsed into a binary variable that assume a value one if an employeeis ‘very satisfied’ or ‘satisfied’ and zero otherwise. 9 Tables A1 and A2 in theAppendix report descriptive statistics and correlation matrix, respectively, of thesatisfaction variables.A summary of the explanatory variables used in the empirical modelling is alsogiven in Table A3 in the Appendix. These include: (i) employee-level correlatessuch as demographic and human capital characteristics, occupation, tenure, payas well correlates reflecting employees’ assessment of the degree of jobflexibility, job-level gender segregation and skill requirement of the job. (ii)workplace-level correlates such as establishment size, industry as well as otherspertaining to the level of gender-, age-, ethnic- and disability segregation at theworkplace.4. A framework of analysisJob satisfaction, or some aspect of it, is typically measured on an ordinal scale,requiring the use of ordered probit or logit as the preferred econometricmodelling strategy. This has led to the almost exclusive reliance on these modelsin the research into the determinants of job satisfaction (e.g. Clark & Oswald1994, Blanchflower 1996, Sousa-Poza & Sousa-Poza 2000, Gazioglu et al. 2006,Maume & Sebastian 2007). The consequence of this heavy reliance on thesemodels, or at least their simpler versions, has been the inability to account forunmeasured/unobserved heterogeneity, something that may be regarded as adrawback of the existing literature on job satisfaction. 10Accounting for such unmeasured heterogeneity is particularly important in thecontext of a linked employer-employee data used in this paper for at least twomain reasons. First, the variance of the estimated coefficients would beunderestimated, thereby leading to wrong inference. Secondly, parameterestimates would be inconsistent if the relationship between the outcome variableof interest and the explanatory variables is non-linear (Rodriguez and Goldman,1995, 2001; Skrondal and Rabe-Hesketh, 2004).As stated in the preceding section, each of the original ordinal satisfactionvariables used in the empirical analysis in this study has been collapsed into abinary variable that assumes a value one if ‘very satisfied’ or ‘satisfied’ and zerootherwise. 11 Thus, letting i index an employee, the underlying continuous latent9 The advantages (& drawback!) that stem from this are explained in the next section.10 There are few exceptions such as Winkelmann & Winkelmann (1998), Clark et al. (2006),Bryson et al. (2004, 2006)11 Although this approach raises the question of efficiency, not exploiting all information in theoriginal satisfaction variable(s), it makes the multilevel modelling much more tractable. That thisallows overcoming problems of estimator inconsistency stemming from the choice of breakingpoint in the ordered probability models (Crouchley 1995) and possible misclassification problemsarising from self-reported measures of job satisfaction that Hausman et al. (1998) refer to aresome of the problems the approach used in this study minimises.7
Page 1 and 2: [Very Preliminary Draft]A multileve
Page 3 and 4: 1. IntroductionEconomists ventured
Page 5: than men (Clark, 1996, 1997; Clark
Page 9 and 10: measure of job satisfaction. 12 By
Page 11 and 12: other hand, having skills that are
Page 13 and 14: 6. ConclusionThis paper has investi
Page 15 and 16: Sales and customer service occ. -0.
Page 17 and 18: (0.269) (0.416) (0.298) (0.288) (0.
Page 19 and 20: Table 1 (cont’d)Sats. with influe
Page 21 and 22: Able to work flexible hrs 0.767 0.8
Page 23 and 24: (0.193) (0.332) (0.250) (0.292) (0.
Page 25 and 26: (0.231)** (0.383) (0.306) (0.196)**
Page 27 and 28: 100 women working p-t -0.361 -0.367
Page 29 and 30: ReferencesAbowd JM, Kramarz F and M
Page 31 and 32: Kersley B., Alpin C., Forth J., Bry
Page 33 and 34: AppendixTable A1 Descriptive statis
Page 35: I am the only one doing the job 0.0

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